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The resistance of wear protective coatings against oxidation is crucial for their use at high temperatures. Here, three nanocomposite AlCr(Si)N coatings with a fixed Al/Cr atomic ratio of 70/30 and a varying Si-content of 0 at.%, 2.5 at.% and 5 at.% were analyzed by differential scanning calorimetry, thermogravimetric analysis and X-ray in order to understand the oxidation behavior depending on their Si-content. Additionally, a partially oxidized AlCrSiN coating with 5 at.% Si on a sapphire substrate was studied across the coating thickness by depth-resolved cross-sectional X-ray nanodiffraction and scanning trans-mission electron microscopy to investigate the elemental composition, morphology, phases and residual stress evolution of the oxide scale and the non-oxidized coating underneath. The results reveal enhanced oxidation properties of the AlCr(Si)N coatings with increasing Si-content, as demonstrated by a retarded onset of oxidation to higher temperatures from 1100°C for AlCrN to 1260°C for the Si-containing coatings and a simultaneous deceleration of the oxidation process. After annealing of the AlCrSiN sample with 5 at.% Si at an extraordinary high temperature of 1400°C for 60 min in ambient air, three zones developed throughout the coating strongly differing in their composition and structure: (i) a dense oxide layer comprising an Al-rich and a Cr-rich zone formed at the very top, followed by (ii) a fine-grained transition zone with incomplete oxidation and (iii) a non-oxidized zone with a porous structure. The varying elemental composition of these zones is furthermore accompanied by micro-structural variations and a complex residual stress development revealed by cross-sectional X-ray nanodiffraction. The results provide a deeper understanding of the oxidation behavior of AlCr(Si)N coatings depending on their Si-content and the associated elemental, microstructural and residual stress evolution during high-temperature oxidation.
A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.
BACKGROUND: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. RESULTS: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. CONCLUSIONS: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.
Abstract Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4‐23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26 application of polygenic scores in clinical practice.